Publications related to Metabolic cost calculations of gait using musculoskeletal energy models, a comparison study

Related publications (31)

Euclid preparation: LXVI. Impact of line-of-sight projections on the covariance between galaxy cluster multi-wavelength observable properties: Insights from hydrodynamic simulations

Context. Cluster cosmology can benefit from combining multi-wavelength studies. In turn, these studies benefit from a characterisation of the correlation coefficients among different mass-observable relations. Aims. In this work, we aim to provide informat ...

EDP Sciences2025

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

Bénédicte Marie Maréchal

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

W B Saunders Co Ltd2024

Weak correlations between visual abilities in healthy older adults, despite long-term performance stability

Michael Herzog, Simona Adele Garobbio

Using batteries of visual tests, most studies have found that there are only weak correlations between the performance levels of the tests. Factor analysis has confirmed these results. This means that a participant excelling in one test may rank low in ano ...

2024

Influence of Ventilation on Formation and Growth of 1-20 nm Particles via Ozone-Human Chemistry

Dusan Licina, Shen Yang, Marouane Merizak, Meixia Zhang

Ozone reaction with human surfaces is an important source of ultrafine particles indoors. However, 1-20 nm particles generated from ozone-human chemistry, which mark the first step of particle formation and growth, remain understudied. Ventilation and indo ...

Amer Chemical Soc2024

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024

Quantitative T2 Mapping of Acute Pancreatitis

Tom Hilbert

Background: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable asse ...

Wiley2024

Novel theory and potential applications of central diastolic pressure decay time constant

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

2024

Euclid: Validation of the MontePython forecasting tools

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Julien Lesgourgues, Slobodan Ilic

Context. The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. Aims. We expand and adjust the mock Euclid likelihoods of t ...

Edp Sciences S A2024

Euclid: The search for primordial features

Yiming Li, Frédéric Courbin, Georges Meylan

Primordial features, in particular oscillatory signals, imprinted in the primordial power spectrum of density perturbations represent a clear window of opportunity for detecting new physics at high-energy scales. Future spectroscopic and photometric measur ...

Edp Sciences S A2024

Unveiling breast cancer metastasis through an advanced X-ray imaging approach

Marianne Liebi

Breast cancer is a significant global health burden, causing a substantial number of deaths. Systemic metastatic tumour cell dissemination is a major cause of poor outcomes. Understanding the mechanisms underlying metastasis is crucial for effective interv ...

Nature Portfolio2024

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

2024

Physiology or Psychology: What Drives Human Emissions of Carbon Dioxide and Ammonia?

Athanasios Nenes, Dusan Licina, Shen Yang, Marouane Merizak

Humans are the primary sources of CO2 and NH3 indoors. Their emission rates may be influenced by human physiological and psychological status. This study investigated the impact of physiological and psychological engagements on the human emissions of CO2 a ...

Amer Chemical Soc2024

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions

Giovanni De Cesare, Paolo Perona, Robin Schroff

This article investigates the performance and accuracy of continuous Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The a ...

2024

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Malte Tewes, Slobodan Ilic, Gianluca Castignani, Alessandro Pezzotta

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

Edp Sciences S A2024

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

A New Analytical Approximation of the Fluid Antenna System Channel

Malek Khammassi

Fluid antenna systems (FAS) are an emerging technology that promises a significant diversity gain even in the smallest spaces. It consists of a freely moving antenna in a small linear space to pick up the strongest received signal. Previous works in the li ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Correlation properties of a one-dimensional repulsive Bose gas at finite temperature

Riccardo Rota

We present a comprehensive study shedding light on how thermal fluctuations affect correlations in a Bose gas with contact repulsive interactions in one spatial dimension. The pair correlation function, the static structure factor, and the one-body density ...

IOP Publishing Ltd2023

Metal-Free Molecular Catalysts for the Oxygen Reduction Reaction: Electron Affinity as an Activity Descriptor

Ganna Gryn'ova, Juliette Veronique Schleicher

Heteroatom-doped polyaromatic hydrocarbons (or nanographenes) are promising molecular electrocatalysts for the oxygen reduction reaction (ORR). Here, we use density functional theory to investigate the first step of the ORR pathway (chemisorption) for a se ...

AMER CHEMICAL SOC2023

Deep excavation of the impact from endogenous and exogenous uncertainties on long-term energy planning

François Maréchal, Xiang Li

Endogenous and exogenous uncertainties exert significant influences on energy planning. In this study, we propose a systematic methodology to excavate the uncertainty space, by combining mix-integer linear programming (MILP), Monte Carlo simulation, and ma ...

ELSEVIER2023